Andres Tennus

Doctoral defense: Maarja Jõeloo "Advances in microarray-based copy number variation discovery and phenotypic associations"

On 31 May, at 10:15 Maarja Jõeloo will defend her doctoral thesis "Advances in microarray-based copy number variation discovery and phenotypic associations".

professor Reedik Mägi
professor Andres Metspalu
professor Andres Salumets
professor Andrew P. Morris (University of Manchester)

Elliott G Rees, PhD (University of Cardiff, Great Britain)

From the biology class we know that every person has one full copy of each DNA molecule from either parent. On closer inspection, however, we observe that several genomic regions deviate from this rule. These regions have undergone additional loss or gain of genomic content, which are called DNA copy number variations (CNVs). They were first discovered in the context of developmental delay and neuropsychiatric disorders, where they exhibited severe pathogenic effects. The current knowledge indicates, however, that CNVs are abundant in the genomes of all individuals. Still, the impact of CNVs on health is considered substantial. In our work we aim to map the effect of CNVs on human traits, by improving CNV analysis methodology and associating CNVs with various diseases and medically relevant phenotypes. CNV detection is challenging and often results in a large proportion of false positive calls. To differentiate true CNVs from false, we have developed a statistical model to estimate CNV quality. We show that our model improves the ability to detect associations between CNVs and traits of interest. The discovery and explorations of such associations comprise the second part of our work. In collaboration with various biobanks and clinical cohorts, we have detected several hundreds of CNV-phenotype associations. We observed that one CNV region can often be linked to multiple seemingly unrelated diseases and traits. For example, we linked a large CNV region in chromosome 16, previously associated with autism, schizophrenia, head circumference and body mass index, to 38 different disease risks and continuous traits. Among them was an association with pubertal timing, which we studied in depth. We found two genes from within the CNV region that we could causally link to pubertal timing. In summary, our work improves CNV detection methodology and maps several CNV regions to phenotypes. With these analyses we take a step closer to fully dissecting the genetics underlying human health.

Thesis defense link in Zoom:

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